Get 20M+ Full-Text Papers For Less Than $1.50/day. Subscribe now for You or Your Team.

Learn More →

Discrete Time Modelling of Disease Incidence Time Series by Using Markov Chain Monte Carlo Methods

Discrete Time Modelling of Disease Incidence Time Series by Using Markov Chain Monte Carlo Methods SummaryA stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the Royal Statistical Society Series C (Applied Statistics) Oxford University Press

Discrete Time Modelling of Disease Incidence Time Series by Using Markov Chain Monte Carlo Methods

Loading next page...
 
/lp/oxford-university-press/discrete-time-modelling-of-disease-incidence-time-series-by-using-Evu0gOemWh

References (44)

Copyright
© 2005 Royal Statistical Society
ISSN
0035-9254
eISSN
1467-9876
DOI
10.1111/j.1467-9876.2005.05366.x
Publisher site
See Article on Publisher Site

Abstract

SummaryA stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities.

Journal

Journal of the Royal Statistical Society Series C (Applied Statistics)Oxford University Press

Published: Jan 21, 2005

Keywords: Disease incidence time series; Markov chain Monte Carlo methods; Stochastic modelling of infectious diseases

There are no references for this article.